research

Research Interests and Contributions

My research focuses on studying and modeling user interactions in various learning contexts. To that end, I follow a combined bottom-up and top-down approach: I engage in exploring data traces of user practice and in seeking patterns that may be backed up by theoretical reasoning. Following this approach, my main contributions are in student modeling and in learning analytics.

Providing personalized and adaptive feedback

To choose the appropriate level of scaffolding and to provide personalized feedback with respect to student's needs, I follow the Vygotskian concept of the Zone of Proximal Development (ZPD). To that end, I have proposed the "Grey Area" approach that acts as a proxy for modeling the ZPD of individual students using learning analytics. According to this approach, the Grey Area is the area where the student model cannot predict with acceptable accuracy the outcome of a student step with respect to correctness and this can provide indication with respect to whether the student is (or is not) in the ZPD.

Exploring the relationship between response time (step duration) and student performance

This work builds on the hypothesis that there is no linear relationship between step duration and correctness. The rationale is that, on the one hand, a student needs a minimum amount of time in order to process the problem, retrieve appropriate information, and to construct a correct response. On the other hand, taking too long to carry out a step could indicate lack of background knowledge, failure to retrieve critical information, and inability to address the step. Therefore, there is a time frame defined by a minimum and a maximum step duration (dtmin and dtmax respectively) in which a student will likely provide the correct answer. Every step that lies outside this time frame will most likely be solved incorrectly or not solved. We identify this time frame as the Zone of Interest (ZOI) and we envision that this concept can be used to provide timely feedback to students and to improve the performance of computational student models.

Research and Teaching Experience

University of Tartu (Senior Researcher / Assistant Professor, current position)

From February 2018, I hold a Senior Researcher (Assistant Professor) in Learning Analytics in the Institute of Education, University of Tartu (Estonia). Here, I explore the use of Learning Analytics (LaTartu) to provide personalized feedback and scaffold learning. I also participate in the Educational Technology Master Program where I am responsible for the "Introduction to Learning Analytics" course (also offered as a master-level course for the Department of Computer Science) and for the "Research in Educational Technology".

Research Activities

As part of my research, I am a member of scientific societies, such as the ISLS (I serve in the Communications Committee since 2017), SOLAR, IAED, ACM and IEEE. I participate in research activities such as program committees, conference organizations, reviewing, etc. I am a reviewer for international journals such as Computers and Education and iJCSCL, and international conferences, such as LAK, CSCL, CSCW, CHI, etc. I serve as a Program Co-Chair for Collabtech 2019 and as a program committee member for conferences (LAK, ICALT, ECTEL). Additionally, I am giving talks, webinars and demonstrations to conferences and other events. You can find the resources for my recent talks here:

December 2018: Invited talk at the European Schoolnet, Learning Research Exchange subcommittee (Talk title: Use of Artificial Intelligence and Machine Learning in OERs and educational portals)

August 2018: Invited talk at the IEEE Estonia Section Meeting at Jäneda, Estonia (talk title: " LA Tartu: Designing a Learning Analytics platform for the University of Tartu… and beyond!")

October 2017: Invited talk at the ScienceEd meetings, University of Pittsburgh